| 基于漂移度的陕西省制造业低碳经济发展水平评价研究 |
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| 引用本文： | 王向英,潘杰义.基于漂移度的陕西省制造业低碳经济发展水平评价研究[J].科技管理研究,2019,39(24). |
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| 作者姓名： | 王向英 潘杰义 |
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| 作者单位： | 西北工业大学管理学院,陕西西安710129;西北工业大学管理学院,陕西西安710129 |
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| 基金项目： | 陕西省软科学、供给侧结构性改革驱动下陕西制造业低碳经济发展路径研究、项目编号：2018KRM063 |
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| 摘 要： | 单一评价方法适用条件各异,都有不可避免的缺陷,为克服单一评价方法的不足,提高评价结果的科学性和可靠性,分别采用主成分分析-AHP法、熵权TOPSIS法、熵权灰色关联投影法对我国30个省市区的制造业低碳经济发展水平进行单一评价,然后构建基于漂移度的组合评价模型,根据相容单一评价结果对我国区域制造业低碳经济发展水平进行组合评价。评价结果显示陕西省排名第21名,处于较落后位置,制造业低碳经济的提升还有相当大的空间,并从制定经济政策、调整能源结构、优化产业结构和重视技术研发四个方面提出促进陕西省制造业低碳发展的政策建议。
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| 关 键 词： | 低碳经济 漂移度 陕西省 制造业 组合评价 |
| 收稿时间： | 2019/2/17 0:00:00 |
| 修稿时间： | 2019/3/9 0:00:00 |
Evaluating the Development Level of Low Carbon Economy in Manufacturing Industry of Shaanxi Province Based on Drift |
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| Abstract: | Each single evaluation method has its own unavoidable shortcomings and different applicable conditions. In order to overcome the shortcomings of the single evaluation method and improve the scientific and reliability of the evaluation results, principal component analysis-AHP method, entropy weight TOPSIS method and Entropy Weight Grey Relational projection method are used to evaluate the low-carbon economic development level of manufacturing industry in 30 provinces and cities in China. Then a combination evaluation model based on drift degree is constructed, and the compatible single evaluation results are combined to realize the combination evaluation of low-carbon economic development level of regional manufacturing industry in China. The evaluation results show that Shaanxi Province ranks 21st and is in a relatively backward position in the whole country. There is still considerable room for improving the low-carbon economy of manufacturing industry. The policy suggestions for promoting the low-carbon development of manufacturing industry in Shaanxi Province are put forward from four aspects: formulating economic policies, adjusting energy structure, optimizing industrial structure and emphasizing technological research and development. |
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| Keywords: | Low carbon economy Drift Shaanxi Manufacturing Combined evaluation |
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